Group and Analyze Data On-the-Fly to Save Time

Update: Dundas BI 5 is here! Download it now to try out the features mentioned below, new advanced visual analytics and built-in integrations, and our superior user experience!

With the release of Dundas BI 5, we’re proud to deliver on our promise of continuously providing visual analytics that simplifies the manner in which you interact with your data. One such way we’ve done so is by providing a simple (yet very, very cool) solution to a common problem around the way data can be organized when being analyzed on the fly.

On-the-fly Dimensions Grouping is, in more or less words, the act of creating custom member (i.e., dimension categories) groups when viewing your data visualizations. But before we get into specifics, let’s see this new feature in action:

What you see in this clip, is Sales data spanning multiple regions and territories whereby products are sold. We’ve visualized the data as a Bar Chart, and have organized it by descending values so that we’re able to see more clearly which regions are leaders and which are bringing up the rear.

You’ll notice that within the middle of the visualization are three (3) bars that reflect Sales values in the United Kingdom, France, and Germany. In our contrived organization, those three (3) countries actually belong to the same territory and are managed by one (1) Sales Manager. So rather than having these values broken down individually, we’d prefer to have them grouped as a single unit.

Before Dundas BI 5, to accomplish this, we’d have to modify our data model by returning to the data cube, creating a calculated expression to check for specific values within a category, and grouping subsequent values into one category. And while this commonly occurring problem has never been the most difficult to solve, it’s often time-consuming and onerous.

Now, with Dundas BI 5, we can simply select the data points we want to group, directly on the visualization using our cursor (or via selection from a drop-down list), and group them with a single click. By being able to do this on-the-fly, the process for how we explore data instantly becomes that much easier. Values can be grouped and un-grouped with minimal effort, and without returning to the data model, eliminating the need to spend excess time preparing data for every question.

“What we’ve done, is devise a very neat way to automatically organize and generate a visual with the right grouping of data, without having to pre-define that in our data preparation layer”Ariel Pohoryles, Director of Product Marketing, Dundas Data Visualization

On-the-fly Dimensions Grouping is not strictly limited to Bar Charts either and can be attributed to other visualizations where grouping is desirable, such as Pie Charts. When analyzing data using Pie Charts, the more slices there are, the more difficult they become to examine. It’s because of this shortcoming that Pie Charts have often been viewed in a negative light in regards to visualization best practices. What’s typically recommended, is to ensure the Pie Chart has no more than three (3) or four (4) slices. This is where grouping should be considered.

With Dundas BI 5, you can now dynamically adjust a Metric Set’s default values, and group data points into precise categories. Take the following video clip for example:

At first glance, the Pie Chart appears cluttered, and its slices are virtually indistinguishable from one another, however, after grouping the data points, the Pie Chart becomes abundantly more digestible. We’ve specified with a few clicks, directly on our Data Analysis Panel, that the Pie Chart should only display the top three (3) slices by size, therefore automatically grouping the remaining data points into an “Other” category/slice.

The ability to group data on-the-fly is incredibly powerful and has multiple practical uses. Grouping is helpful when correcting data errors (i.e., grouping Toronto and TO into one data point, or grouping similar datum to form single data points such as the above example), as well as answering questions of hypothetical nature, such as “What if we were to combine North and South America?”